Acoustic emissions and surface vibrations monitoring, have previously been used to investigate and control the performance of mineral processing unit operations. Control of power draft in autogenous grinding (AG) mills and SAG mills has traditionally been via load cells estimating the charge mass. However, acoustic emissions from dual microphone systems have been used to monitor the changing level of impact of the charge on an AG mill shell. A pair of microphones were mounted at approximately 30° from the bottom and 30° from the centre line of the mill. The position of the microphones was such that the upper unit was above the normal level of charge impact on the liner while the lower unit was below the same. If the load level rises in the mill, the point of impact moves toward the upper microphone and away from the lower. If the load level drops, the converse applies. Therefore changes in load level are registered by variation in the comparative sound intensity at the two microphones. The resulting estimate of the load volume is correlated with the power draft and used to control the feed rate in order to maintain optimal milling conditions and maximum power draft. It was shown that microphone signals are much more sensitive to load change than the load cell. However, the method is crude in that it uses sound intensity at only two fixed points outside the mill. The intensity of sound at these two positions may be considerably influenced by events both outside the mill and at a variety of locations within the mill. The technique therefore only permits qualitative investigation of the state of the charge inside the mill.
Acoustic emissions are also known to be indicators of pulp density and viscosity. The dual microphone study of AG mill acoustic emissions showed that the sound intensity emanating from the charge region (lower microphone) was correlated with the pulp density. The lower microphone sound intensity was used to control water addition rate. Low pulp density was thought to result in higher transmission of noise and increased media/media and media/liner collision events. Meanwhile at higher pulp density grinding action was thought to be inhibited by the increased pulp viscosity, reflected in lower noise intensity. Estimation of effective pulp density and viscosity via the magnitude of acoustic emissions has also been achieved for laboratory batch ball mills. Results suggest that changes in mill noise can be used to identify the pulp rheological regime and potentially used to optimise grinding efficiency. Mill sound noise has also been shown to indicate charge size distribution, ore breakage rates, and ore character in batch ball mills (Watson, 1985; Watson and Morrison, 1985).
Acoustic emissions monitoring has also been used to analyse hydrocyclone performance. A shear structure piezoelectric type acoustic sensor was mounted halfway along the conical section of a 5″ hydrocyclone body. The digitised signal was sampled at 2000 Hz and a Past Fourier Transform (FFT) algorithm used to derive the Power Spectral Density function (PSD) for analysis of acoustic emission characteristics in the frequency domain. Features of acoustic emissions were analysed for varying feed solids concentrations and pressure. Results indicated significant spectral features in the frequency range from DC to about 50 Hz and between 30 and 45 Hz. The height of these spectral features was sensitive to operating conditions. It was conjectured that the spectral structure is related to features of the hydrodynamics inside the hydrocyclone local to the sensor. A stepwise regression analysis technique was used to derive linear relationships between the operating parameters of the cyclone and the spectral and statistical characteristics of the acoustic emissions. The signal measures used in this analysis were for the time domain maxima, mean, standard deviation, rootmean-square, skewness and kurtosis, and for the frequency domain the first 52 spectral components of the PSI). The model was then used for reasonable predictions of hydrocyclone feed pressure, solids concentration, mass and volume flow rates and underflow concentration. This investigation showed that non-invasive acoustic emission measurement coupled with multivariate statistical analysis techniques are a useful tool for monitoring the bulk characteristics of both process and equipment, in this case hydrocyclone operation.
Vibration monitoring and signal analysis have been used to study the feed distribution characteristics of parallel Dense Medium (DM) cyclones in a coal preparation plant. The method is based on the concept that the monitoring of vibrations on the external surface of the cyclone can yield the frequency and strength of particle impacts (particularly for larger particles near entry and exit points). Accelerometers for measuring vibrational accelerations were mounted near the feed inlet, underflow spigot and overflow cap. Relatively large vibrations were noted in the region of the overflow cap, reflecting the energy of particle/wall impacts in that region due to the flow regime within the cyclone. Results indicated that vibration measurements are a superposition of a large number of transients caused by individual particle impacts.